@dollhousemcp/mcp-server
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DollhouseMCP - A Model Context Protocol (MCP) server that enables dynamic AI persona management from markdown files, allowing Claude and other compatible AI assistants to activate and switch between different behavioral personas.
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TypeScript
/**
* Rating management system for element evaluation and feedback processing.
* Handles both AI evaluation and user feedback to drive continuous improvement.
*/
import { IElement, UserFeedback, FeedbackContext } from './IElement.js';
import { ElementType } from '../../portfolio/types.js';
export interface IRatingManager {
evaluateElement(element: IElement, metrics: PerformanceMetrics): Promise<number>;
processFeedback(element: IElement, feedback: string, context?: FeedbackContext): Promise<void>;
analyzeDelta(element: IElement): DeltaAnalysis;
suggestImprovements(element: IElement): Improvement[];
getAggregateRatings(elementType?: ElementType): AggregateRatings;
getRatingHistory(elementId: string): RatingHistoryEntry[];
evaluateMany(elements: IElement[], metrics: PerformanceMetrics): Promise<Map<string, number>>;
}
export interface PerformanceMetrics {
taskCompletion: number;
responseTime: number;
errorRate: number;
resourceUsage?: ResourceMetrics;
customMetrics?: Record<string, number>;
}
export interface ResourceMetrics {
tokenCount?: number;
apiCalls?: number;
computeTime?: number;
memoryUsage?: number;
}
export interface DeltaAnalysis {
delta: number;
significance: 'high' | 'medium' | 'low' | 'none';
possibleReasons: string[];
recommendations: string[];
confidence: number;
}
export interface Improvement {
area: string;
currentScore: number;
targetScore: number;
suggestion: string;
priority: 'high' | 'medium' | 'low';
estimatedImpact: number;
}
export interface AggregateRatings {
elementType?: ElementType;
count: number;
averageAiRating: number;
averageUserRating: number;
averageDelta: number;
topRated: ElementRatingSummary[];
bottomRated: ElementRatingSummary[];
mostImproved: ElementRatingSummary[];
distribution: RatingDistribution;
}
export interface ElementRatingSummary {
elementId: string;
elementName: string;
aiRating: number;
userRating?: number;
ratingCount: number;
trend: 'improving' | 'declining' | 'stable';
}
export interface RatingDistribution {
stars1: number;
stars2: number;
stars3: number;
stars4: number;
stars5: number;
}
export interface RatingHistoryEntry {
timestamp: Date;
aiRating: number;
userRating?: number;
metrics?: PerformanceMetrics;
feedback?: UserFeedback;
version: string;
}
export interface IFeedbackProcessor {
process(feedback: string): Promise<ProcessedFeedback>;
analyzeSentiment(text: string): Promise<'positive' | 'negative' | 'neutral'>;
inferRating(text: string): Promise<number | null>;
extractSuggestions(text: string): Promise<string[]>;
}
export interface ProcessedFeedback {
originalFeedback: string;
sentiment: 'positive' | 'negative' | 'neutral';
inferredRating?: number;
confidence: number;
keywords: string[];
suggestions: string[];
entities: FeedbackEntity[];
}
export interface FeedbackEntity {
type: 'feature' | 'issue' | 'praise' | 'criticism';
text: string;
relevance: number;
}
export interface IRatingCalculator<T extends IElement> {
calculate(element: T, metrics: PerformanceMetrics): number;
getWeights(): RatingWeights;
adjustWeights(feedback: ProcessedFeedback[]): RatingWeights;
}
export interface RatingWeights {
effectiveness: number;
reliability: number;
usability: number;
[key: string]: number;
}
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